English
Related papers

Related papers: Hamiltonian transformation for accurate and effici…

200 papers

We derive electronic tight-binding Hamiltonians for strained graphene, hexagonal boron nitride and transition metal dichalcogenides based on Wannier transformation of {\it ab initio} density functional theory calculations. Our microscopic…

Mesoscale and Nanoscale Physics · Physics 2018-08-14 Shiang Fang , Stephen Carr , Miguel A. Cazalilla , Efthimios Kaxiras

Utilizing the sparsity of the electronic structure problem, fragmentation methods have been researched for decades with great success, pushing the limits of ab initio quantum chemistry ever further. Recently, this set of methods was…

Chemical Physics · Physics 2024-12-03 Marco Bauer , Andreas Dreuw , Anthony D. Dutoi

Accurate orthogonal tight-binding Hamiltonians are constructed for ferromagnetic SrRuO$_3$ and the layered perovskite superconductor, Sr$_2$RuO$_4$ by fitting to all-electron full-potential local density band structures obtained by the…

Materials Science · Physics 2009-10-31 I. I. Mazin , D. A. Papaconstantopoulos , D. J. Singh

We consider a wide class of semi linear Hamiltonian partial differential equa- tions and their approximation by time splitting methods. We assume that the nonlinearity is polynomial, and that the numerical tra jectory remains at least uni-…

Numerical Analysis · Mathematics 2009-12-16 Erwan Faou , Benoit Grebert

The development of machine learning sheds new light on the problem of statistical thermodynamics in multicomponent alloys. However, a data-driven approach to construct the effective Hamiltonian requires sufficiently large data sets, which…

Materials Science · Physics 2020-01-01 Xianglin Liu , Jiaxin Zhang , Markus Eisenbach , Yang Wang

Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schr\"odinger equation are at the heart of computational materials science. In that respect the coupled cluster hierarchy of methods plays a…

Materials Science · Physics 2022-01-11 Tina N. Mihm , Tobias Schäfer , Sai Kumar Ramadugu , Andreas Grüneis , James J. Shepherd

Reducing the complexity of quantum algorithms to treat quantum chemistry problems is essential to demonstrate an eventual quantum advantage of Noisy-Intermediate Scale Quantum (NISQ) devices over their classical counterpart. Significant…

Quantum Physics · Physics 2022-12-07 Emiel Koridon , Saad Yalouz , Bruno Senjean , Francesco Buda , Thomas E. O'Brien , Lucas Visscher

The reduction of Hamiltonian systems aims to build smaller reduced models, valid over a certain range of time and parameters, in order to reduce computing time. By maintaining the Hamiltonian structure in the reduced model, certain…

Numerical Analysis · Mathematics 2024-09-17 Raphaël Côte , Emmanuel Franck , Laurent Navoret , Guillaume Steimer , Vincent Vigon

Supersymmetric extensions of the 1D and 2D Swanson models are investigated by applying the conformal bridge transformation (CBT) to the first order Berry-Keating Hamiltonian multiplied by $i$ and its conformally neutral enlargements. The…

High Energy Physics - Theory · Physics 2022-09-01 Luis Inzunza , Mikhail S. Plyushchay

This chapter concerns with the recent development of a new DFT methodology for accurate, reliable prediction of many-electron systems. Background, need for such a scheme, major difficulties encountered, as well as their potential remedies…

Chemical Physics · Physics 2019-04-19 Amlan K. Roy

Hierarchical modulation (HM) is able to provide different levels of protection for data streams and achieve a rate region that cannot be realized by traditional orthogonal schemes, such as time division (TD). Nevertheless, criterions and…

Information Theory · Computer Science 2016-10-19 Baicen Xiao , Kexin Xiao , Zhiyong Chen , Hui Liu

We present a new method for calculating electronic states in low-dimensional semiconductor heterostructures, which is based on the real-space Hamiltonian in the envelope function approximation. The numerical implementation of the method is…

Mesoscale and Nanoscale Physics · Physics 2011-06-01 Yong-Hee Cho , Alexey Belyanin

Variational approaches are among the most powerful modern techniques to approximately solve quantum many-body problems. These encompass both variational states based on tensor or neural networks, and parameterized quantum circuits in…

Strongly Correlated Electrons · Physics 2021-02-02 Kevin Zhang , Samuel Lederer , Kenny Choo , Titus Neupert , Giuseppe Carleo , Eun-Ah Kim

We propose Walsh-Hadamard Transform Division Multiplexing (WHTDM), a multicarrier waveform that replaces the conventional IFFT/FFT pair in OFDM with a real-valued, unitary Walsh-Hadamard transform (WHT). WHTDM inherits the CP-OFDM…

Signal Processing · Electrical Eng. & Systems 2026-05-15 Wang Hao , Yuan Zhonghao , Chi Yonggang , Zhang Kuang , Tan Chenxing , Yu Jiaxing

In this paper, we present a new approach for the exact calculation of band structure in one-dimensional periodic media, such as photonic crystals and superlattices, based on the recently reported differential transfer matrix method (DTMM).…

Mathematical Physics · Physics 2009-11-10 Sina Khorasani , Ali Adibi

The exploration of quantum phenomena in complex materials such as moir\'e superlattices is limited by the O(N^3) scaling of conventional electronic structure methods. Here we introduce a high-performance tight-binding framework that reduces…

Computational Physics · Physics 2026-01-21 Zichong Zhang , Shuze Zhu

We describe a method that allows for a practical application of the theory of pseudo-Hermitian operators to PT-symmetric systems defined on a complex contour. We apply this method to study the Hamiltonians $H=p^2+x^2(ix)^\nu$ with…

Quantum Physics · Physics 2007-05-23 Ali Mostafazadeh

We consider the Fast Fourier Transform (FFT) based numerical method for thin film magnetization problems [Vestg{\aa}rden and Johansen, SuST, 25 (2012) 104001], compare it with the finite element methods, and evaluate its accuracy. Proposed…

Computational Physics · Physics 2018-05-09 Leonid Prigozhin , Vladimir Sokolovsky

Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations when the underlying lattices can be represented as small…

We present a method for the calculation of electronic structure of systems that contain tens of thousands of atoms. The method is based on the division of the system into mutually overlapping fragments and the representation of the…

Materials Science · Physics 2011-03-09 Nenad Vukmirović , Lin-Wang Wang